IEEE Transactions on Information Theory

Volume 64 Issue 2 • Feb. 2018

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  • Table of contents

    Publication Year: 2018, Page(s):C1 - C4
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  • IEEE Transactions on Information Theory publication information

    Publication Year: 2018, Page(s): C2
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  • Robust Nonnegative Sparse Recovery and the Nullspace Property of 0/1 Measurements

    Publication Year: 2018, Page(s):689 - 703
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (484 KB) | HTML iconHTML

    We investigate recovery of nonnegative vectors from non-adaptive compressive measurements in the presence of noise of unknown power. In the absence of noise, existing results in the literature identify properties of the measurement that assure uniqueness in the non-negative orthant. By linking such uniqueness results to nullspace properties, we deduce uniform and robust compressed sensing guarante... View full abstract»

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  • Blind Demixing and Deconvolution at Near-Optimal Rate

    Publication Year: 2018, Page(s):704 - 727
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (514 KB) | HTML iconHTML

    We consider simultaneous blind deconvolution of r source signals from their noisy superposition, a problem also referred to blind demixing and deconvolution. This signal processing problem occurs in the context of the Internet of Things where a massive number of sensors sporadically communicate only short messages over unknown channels. We show that robust recovery of message and channel vectors c... View full abstract»

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  • On the Algorithmization of Janashia-Lagvilava Matrix Spectral Factorization Method

    Publication Year: 2018, Page(s):728 - 737
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (615 KB) | HTML iconHTML

    We consider three different ways of algorithmization of the Janashia-Lagvilava spectral factorization method. The first algorithm is faster than the second one, however, it is only suitable for matrices of low dimension. The second algorithm, on the other hand, can be applied to matrices of substantially larger dimension. The third algorithm is a superfast implementation of the method, but only wo... View full abstract»

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  • On the Geometric Ergodicity of Metropolis-Hastings Algorithms for Lattice Gaussian Sampling

    Publication Year: 2018, Page(s):738 - 751
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (796 KB) | HTML iconHTML

    Sampling from the lattice Gaussian distribution has emerged as an important problem in coding, decoding, and cryptography. In this paper, the classic Metropolis-Hastings (MH) algorithm in Markov chain Monte Carlo methods is adopted for lattice Gaussian sampling. Two MH-based algorithms are proposed, which overcome the limitation of Klein's algorithm. The first one, referred to as the independent M... View full abstract»

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  • Gaussian Distributions on Riemannian Symmetric Spaces: Statistical Learning With Structured Covariance Matrices

    Publication Year: 2018, Page(s):752 - 772
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (942 KB) | HTML iconHTML

    The Riemannian geometry of covariance matrices has been essential to several successful applications, in computer vision, biomedical signal and image processing, and radar data processing. For these applications, an important ongoing challenge is to develop Riemannian-geometric tools which are adapted to structured covariance matrices. This paper proposes to meet this challenge by introducing a ne... View full abstract»

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  • Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow

    Publication Year: 2018, Page(s):773 - 794
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2736 KB) | HTML iconHTML

    This paper presents a new algorithm, termed truncated amplitude flow (TAF), to recover an unknown vector x from a system of quadratic equations of the form yi = |〈ai, x〉|2, where ai's are given random measurement vectors. This problem is known to be NP-hard in general. We prove that as soon as the number of equations is on the order of the ... View full abstract»

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  • Semiparametric Two-Component Mixture Models When One Component Is Defined Through Linear Constraints

    Publication Year: 2018, Page(s):795 - 830
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1476 KB) | HTML iconHTML

    We propose a structure of a semiparametric two-component mixture model when one component is parametric and the other is defined through linear constraints on either its distribution function or its quantile measure. Estimation of a two-component mixture model with an unknown component is very difficult when no particular assumption is made on the structure of the unknown component. A symmetry ass... View full abstract»

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  • Learning to Detect an Oddball Target

    Publication Year: 2018, Page(s):831 - 852
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1007 KB) | HTML iconHTML

    We consider the problem of detecting an odd process among a group of Poisson point processes, all having the same rate except the odd process. The actual rates of the odd and non-odd processes are unknown to the decision maker. We consider a time-slotted sequential detection scenario where, at the beginning of each slot, the decision maker can choose which process to observe during that time slot.... View full abstract»

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  • Cluster-Seeking James–Stein Estimators

    Publication Year: 2018, Page(s):853 - 874
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1191 KB) | HTML iconHTML

    This paper considers the problem of estimating a high-dimensional vector of parameters Θ ∈ Rn from a noisy observation. The noise vector is independent identically distributed Gaussian with known variance. For a squared-error loss function, the James-Stein (JS) estimator is known to dominate the simple maximum-likelihood (ML) estimator when the dimension n exceeds two. The JS-estimat... View full abstract»

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  • Minimum Rates of Approximate Sufficient Statistics

    Publication Year: 2018, Page(s):875 - 888
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (405 KB) | HTML iconHTML

    Given a sufficient statistic for a parametric family of distributions, one can estimate the parameter without access to the data. However, the memory or code size for storing the sufficient statistic may nonetheless still be prohibitive. Indeed, for n independent samples drawn from a k-nomial distribution with d = k - 1 degrees of freedom, the length of the code scales as d log n + O(1). In many a... View full abstract»

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  • New Constructions of Optimal Locally Recoverable Codes via Good Polynomials

    Publication Year: 2018, Page(s):889 - 899
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (248 KB) | HTML iconHTML

    In recent literature, a family of optimal linear locally recoverable codes (LRC codes) that attain the maximum possible distance (given code length, cardinality, and locality) is presented. The key ingredient for constructing such optimal linear LRC codes is the so-called r-good polynomials, where r is equal to the locality of the LRC code. However, given a prime p, known constructions of r-good p... View full abstract»

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  • Repairing Algebraic Geometry Codes

    Publication Year: 2018, Page(s):900 - 908
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (276 KB) | HTML iconHTML

    Minimum storage regenerating codes have minimum storage of data in each node and therefore are maximal distance separable (for short) codes. Thus, the number of nodes is upper-bounded by 2b, where ú is the bits of data stored in each node. From both theoretical and practical points of view (see the details in Section 1), it is natural to consider regenerating codes that nearly h... View full abstract»

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  • Linear Size Constant-Composition Codes Meeting the Johnson Bound

    Publication Year: 2018, Page(s):909 - 917
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (681 KB) | HTML iconHTML

    The Johnson-type upper bound on the maximum size of a code of length n, distance d = 2w - 1, and constant n composition w̅ is [n/w1] the largest component of w̅. Recently, Chee et al. proved that this upper bound can be achieved for all constant-composition codes of sufficiently large lengths. Let Nccc(w) be the smallest such length. The determination of Nc... View full abstract»

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  • A Constrained Coding Scheme for Correcting Asymmetric Magnitude-1 Errors in $q$ -Ary Channels

    Publication Year: 2018, Page(s):918 - 932
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1250 KB) | HTML iconHTML

    We present a constraint-coding scheme to correct asymmetric magnitude-1 errors in multi-level non-volatile memories. For large numbers of such errors, the scheme is shown to deliver better correction capability compared with known alternatives, while admitting low-complexity of decoding. Our results include an algebraic formulation of the constraint, necessary and sufficient conditions for correct... View full abstract»

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  • Staircase Codes for Secret Sharing With Optimal Communication and Read Overheads

    Publication Year: 2018, Page(s):933 - 943
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (627 KB) | HTML iconHTML

    We study the communication efficient secret sharing (CESS) problem. A classical threshold secret sharing scheme encodes a secret into n shares given to n parties, such that any set of at least t, t <; n, parties can reconstruct the secret, and any set of at most z, z <; t <; n, colluding parties cannot obtain any information about the secret. A CESS scheme satisfies the previous propertie... View full abstract»

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  • On Decoding Rank-Metric Codes Over Large Fields

    Publication Year: 2018, Page(s):944 - 951
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (661 KB) | HTML iconHTML

    A decoding algorithm is presented for a rank-metric array codes that are based on diagonal interleaving of maximum-distance separable codes. With respect to this metric, such array codes are known to be optimal when the underlying field is algebraically closed. It is also shown that for any list decoding radius that is smaller than the minimum rank distance, the list size can be bounded from above... View full abstract»

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  • Algebraic Decoding of Cyclic Codes Using Partial Syndrome Matrices

    Publication Year: 2018, Page(s):952 - 971
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1874 KB) | HTML iconHTML

    Cyclic codes have been widely used in many applications of communication systems and data storage systems. This paper proposes a new procedure for decoding cyclic codes up to actual minimum distance. The decoding procedure consists of two steps: 1) computation of known syndromes and 2) computation of error positions and error values simultaneously. To do so, a matrix whose all entries are syndrome... View full abstract»

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  • Fast Decoding of Expander Codes

    Publication Year: 2018, Page(s):972 - 978
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (835 KB) | HTML iconHTML

    Expander codes are Tanner codes defined on sparse graphs that have good expansion properties. Sipser and Spielman (1996) showed that there is a linear-time decoding algorithm for expander codes when the vertex expansion is at least 3/4 and the number of errors corrected is a constant fraction of the code length. Later, Feldman et al. (2007) gave a decoding algorithm that allows the expansion to be... View full abstract»

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  • A Polynomial-Time Algorithm for Pliable Index Coding

    Publication Year: 2018, Page(s):979 - 999
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (861 KB) | HTML iconHTML

    In pliable index coding, we consider a server withm messages and n clients, where each client has as side information a subset of the messages. We seek to minimize the number of broadcast transmissions, so that each client can recover any one unknown message she does not already have. Previous work has shown that the pliable index coding problem is NP-hard and requires at most O(log2(n)... View full abstract»

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  • Private Information Retrieval from MDS Coded Data With Colluding Servers: Settling a Conjecture by Freij-Hollanti et al.

    Publication Year: 2018, Page(s):1000 - 1022
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (777 KB) | HTML iconHTML

    A (K, N, T, Kc) instance of private information retrieval from MDS coded data with colluding servers (in short, MDS-TPIR), is comprised of K messages and N distributed servers. Each message is separately encoded through a (Kc, N) MDS storage code. A user wishes to retrieve one message, as efficiently as possible, while revealing no information about the desired message index ... View full abstract»

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  • Cut-Set Bound is Loose for Gaussian Relay Networks

    Publication Year: 2018, Page(s):1023 - 1037
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (553 KB) | HTML iconHTML

    The cut-set bound developed by Cover and El Gamal in 1979 has since remained the best known upper bound on the capacity of the Gaussian relay channel. We develop a new upper bound on the capacity of the Gaussian primitive relay channel, which is tighter than the cut-set bound. Our proof uses Gaussian measure concentration to establish geometric relations, satisfied with high probability, between t... View full abstract»

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  • Algorithmic Aspects of Optimal Channel Coding

    Publication Year: 2018, Page(s):1038 - 1045
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (188 KB) | HTML iconHTML

    A central question in information theory is to determine the maximum success probability that can be achieved in sending a fixed number of messages over a noisy channel. This was first studied in the pioneering work of Shannon, who established a simple expression characterizing this quantity in the limit of multiple independent uses of the channel. Here, we consider the general setting with only o... View full abstract»

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  • The MIMO Wiretap Channel Decomposed

    Publication Year: 2018, Page(s):1046 - 1063
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (606 KB) | HTML iconHTML

    The problem of sending a secret message over the Gaussian multiple-input multiple-output (MIMO) wiretap channel is studied. While the capacity of this channel is known, it is not clear how to construct optimal coding schemes that achieve this capacity. In this paper, we use linear operations along with successive interference cancellation to attain effective parallel single-antenna wiretap channel... View full abstract»

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Aims & Scope

IEEE Transactions on Information Theory publishes papers concerned with the transmission, processing, and utilization of information.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Prakash Narayan 

Department of Electrical and Computer Engineering